GPU-Based Parallel Implementation of Swarm Intelligence Algorithms

✍ Scribed by Ying Tan

• Publisher: Morgan Kaufmann
• Year: 2016
• Tongue: English
• Leaves: 239
• Edition: 1
• Category: Library

✦ Synopsis

GPU-based Parallel Implementation of Swarm Intelligence Algorithms combines and covers two emerging areas attracting increased attention and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform.

GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone.

This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research.

• Presents a concise but sufficient introduction to general-purpose GPU computing which can help the layman become familiar with this emerging computing technique
• Describes implementation details, such as parallel models and performance metrics, so readers can easily utilize the techniques to accelerate their algorithmic programs
• Appeals to readers from the domain of high performance computing (HPC) who will find the relatively young research domain of swarm intelligence very interesting
• Includes many real-world applications, which can be of great help in deciding whether or not swarm intelligence algorithms or GPGPU is appropriate for the task at hand

✦ Table of Contents

Content:
Front matter,Copyright,Dedication,Preface,Acknowledgments,AcronymsEntitled to full textChapter 1 - Introduction, Pages 1-7
Chapter 2 - GPGPU: General-Purpose Computing on the GPU, Pages 9-31
Chapter 3 - Parallel Models, Pages 33-48
Chapter 4 - Performance Metrics, Pages 49-55
Chapter 5 - Implementation Considerations, Pages 57-62
Chapter 6 - GPU-Based Particle Swarm Optimization, Pages 63-91
Chapter 7 - GPU-Based Fireworks Algorithm, Pages 93-110
Chapter 8 - Attract-Repulse Fireworks Algorithm Using Dynamic Parallelism, Pages 111-132
Chapter 9 - Other Typical Swarm Intelligence Algorithms Based on GPUs, Pages 133-145
Chapter 10 - GPU-Based Random Number Generators, Pages 147-165
Chapter 11 - Applications, Pages 167-177
Chapter 12 - A CUDA-Based Test Suit, Pages 179-206
Appendix A - Figures and Tables, Pages 207, 209-214
Appendix B - Resources, Pages 215-216
Appendix C - Table of Symbols, Pages 217-218
References, Pages 219-230
Index, Pages 231-236

✦ Subjects

Graphics processing units;Parallel processing (Electronic computers);Swarm intelligence